Comparison of onboard low-field magnetic resonance imaging versus onboard computed tomography for anatomy visualization in radiotherapy.

BACKGROUND: Onboard magnetic resonance imaging (OB-MRI) for daily localization and adaptive radiotherapy has been under development by several groups. However, no clinical studies have evaluated whether OB-MRI improves visualization of the target and organs at risk (OARs) compared to standard onboard computed tomography (OB-CT). This study compared visualization of patient anatomy on images acquired on the MRI-(60)Co ViewRay system to those acquired with OB-CT. MATERIAL AND METHODS: Fourteen patients enrolled on a protocol approved by the Institutional Review Board (IRB) and undergoing image-guided radiotherapy for cancer in the thorax (n = 2), pelvis (n = 6), abdomen (n = 3) or head and neck (n = 3) were imaged with OB-MRI and OB-CT. For each of the 14 patients, the OB-MRI and OB-CT datasets were displayed side-by-side and independently reviewed by three radiation oncologists. Each physician was asked to evaluate which dataset offered better visualization of the target and OARs. A quantitative contouring study was performed on two abdominal patients to assess if OB-MRI could offer improved inter-observer segmentation agreement for adaptive planning. RESULTS: In total 221 OARs and 10 targets were compared for visualization on OB-MRI and OB-CT by each of the three physicians. The majority of physicians (two or more) evaluated visualization on MRI as better for 71% of structures, worse for 10% of structures, and equivalent for 14% of structures. 5% of structures were not visible on either. Physicians agreed unanimously for 74% and in majority for > 99% of structures. Targets were better visualized on MRI in 4/10 cases, and never on OB-CT. CONCLUSION: Low-field MR provides better anatomic visualization of many radiotherapy targets and most OARs as compared to OB-CT. Further studies with OB-MRI should be pursued.

Process-based quality management for clinical implementation of adaptive radiotherapy.

PURPOSE: Intensity-modulated adaptive radiotherapy (ART) has been the focus of considerable research and developmental work due to its potential therapeutic benefits. However, in light of its unique quality assurance (QA) challenges, no one has described a robust framework for its clinical implementation. In fact, recent position papers by ASTRO and AAPM have firmly endorsed pretreatment patient-specific IMRT QA, which limits the feasibility of online ART. The authors aim to address these obstacles by applying failure mode and effects analysis (FMEA) to identify high-priority errors and appropriate risk-mitigation strategies for clinical implementation of intensity-modulated ART. METHODS: An experienced team of two clinical medical physicists, one clinical engineer, and one radiation oncologist was assembled to perform a standard FMEA for intensity-modulated ART. A set of 216 potential radiotherapy failures composed by the forthcoming AAPM task group 100 (TG-100) was used as the basis. Of the 216 failures, 127 were identified as most relevant to an ART scheme. Using the associated TG-100 FMEA values as a baseline, the team considered how the likeliness of occurrence (O), outcome severity (S), and likeliness of failure being undetected (D) would change for ART. New risk priority numbers (RPN) were calculated. Failures characterized by RPN ≥ 200 were identified as potentially critical. RESULTS: FMEA revealed that ART RPN increased for 38% (n = 48/127) of potential failures, with 75% (n = 36/48) attributed to failures in the segmentation and treatment planning processes. Forty-three of 127 failures were identified as potentially critical. Risk-mitigation strategies include implementing a suite of quality control and decision support software, specialty QA software/hardware tools, and an increase in specially trained personnel. CONCLUSIONS: Results of the FMEA-based risk assessment demonstrate that intensity-modulated ART introduces different (but not necessarily more) risks than standard IMRT and may be safely implemented with the proper mitigations.

Segmentation precision of abdominal anatomy for MRI-based radiotherapy.

The limited soft tissue visualization provided by computed tomography, the standard imaging modality for radiotherapy treatment planning and daily localization, has motivated studies on the use of magnetic resonance imaging (MRI) for better characterization of treatment sites, such as the prostate and head and neck. However, no studies have been conducted on MRI-based segmentation for the abdomen, a site that could greatly benefit from enhanced soft tissue targeting. We investigated the interobserver and intraobserver precision in segmentation of abdominal organs on MR images for treatment planning and localization. Manual segmentation of 8 abdominal organs was performed by 3 independent observers on MR images acquired from 14 healthy subjects. Observers repeated segmentation 4 separate times for each image set. Interobserver and intraobserver contouring precision was assessed by computing 3-dimensional overlap (Dice coefficient [DC]) and distance to agreement (Hausdorff distance [HD]) of segmented organs. The mean and standard deviation of intraobserver and interobserver DC and HD values were DC(intraobserver) = 0.89 ± 0.12, HD(intraobserver) = 3.6mm ± 1.5, DC(interobserver) = 0.89 ± 0.15, and HD(interobserver) = 3.2mm ± 1.4. Overall, metrics indicated good interobserver/intraobserver precision (mean DC > 0.7, mean HD < 4mm). Results suggest that MRI offers good segmentation precision for abdominal sites. These findings support the utility of MRI for abdominal planning and localization, as emerging MRI technologies, techniques, and onboard imaging devices are beginning to enable MRI-based radiotherapy.

Quality Assurance with Plan Veto: reincarnation of a record and verify system and its potential value.

PURPOSE: To quantify the potential impact of the Integrating the Healthcare Enterprise-Radiation Oncology Quality Assurance with Plan Veto (QAPV) on patient safety of external beam radiation therapy (RT) operations. METHODS AND MATERIALS: An institutional database of events (errors and near-misses) was used to evaluate the ability of QAPV to prevent clinically observed events. We analyzed reported events that were related to Digital Imaging and Communications in Medicine RT plan parameter inconsistencies between the intended treatment (on the treatment planning system) and the delivered treatment (on the treatment machine). Critical Digital Imaging and Communications in Medicine RT plan parameters were identified. Each event was scored for importance using the Failure Mode and Effects Analysis methodology. Potential error occurrence (frequency) was derived according to the collected event data, along with the potential event severity, and the probability of detection with and without the theoretical implementation of the QAPV plan comparison check. Failure Mode and Effects Analysis Risk Priority Numbers (RPNs) with and without QAPV were compared to quantify the potential benefit of clinical implementation of QAPV. RESULTS: The implementation of QAPV could reduce the RPN values for 15 of 22 (71%) of evaluated parameters, with an overall average reduction in RPN of 68 (range, 0-216). For the 6 high-risk parameters (>200), the average reduction in RPN value was 163 (range, 108-216). The RPN value reduction for the intermediate-risk (200 > RPN > 100) parameters was (0-140). With QAPV, the largest RPN value for "Beam Meterset" was reduced from 324 to 108. The maximum reduction in RPN value was for Beam Meterset (216, 66.7%), whereas the maximum percentage reduction was for Cumulative Meterset Weight (80, 88.9%). CONCLUSION: This analysis quantifies the value of the Integrating the Healthcare Enterprise-Radiation Oncology QAPV implementation in clinical workflow. We demonstrate that although QAPV does not provide a comprehensive solution for error prevention in RT, it can have a significant impact on a subset of the most severe clinically observed events.

Comparison of dose decrement from intrafraction motion for prone and supine prostate radiotherapy.

BACKGROUND AND PURPOSE: Dose effects of intrafraction motion during prone prostate radiotherapy are unknown. We compared prone and supine treatment using real-time tracking data to model dose coverage. MATERIAL AND METHODS: Electromagnetic tracking data were analyzed for 10 patients treated prone, and 15 treated supine, with IMRT for localized prostate cancer. Plans were generated using 0 mm, 3 mm, and 5mm PTV expansions. Manual beam-hold interventions were applied to reposition the patient when translations exceeded a predetermined threshold. A custom software application (SWIFTER) used intrafraction tracking data acquired during beam-on model delivered prostate dose, by applying rigid body transformations to the prostate structure contoured at simulation within the planned dose cloud. The delivered minimum prostate dose as a percentage of planned dose (Dmin%), and prostate volume covered by the prescription dose as a percentage of the planned volume (VRx%) were compared for prone and supine treatment. RESULTS: Dmin% was reduced for prone treatment for 0 (p=0.02) and 3 mm (p=0.03) PTV margins. VRx% was reduced for prone treatment only for 0mm margins (p=0.002). No significant differences were found using 5 mm margins. CONCLUSIONS: Intrafraction motion has a greater impact on target coverage for prone compared to supine prostate radiotherapy. PTV margins of 3 mm or less correlate with a significant decrease in delivered dose for prone treatment.

Practical method of adaptive radiotherapy for prostate cancer using real-time electromagnetic tracking.

PURPOSE: We have created an automated process using real-time tracking data to evaluate the adequacy of planning target volume (PTV) margins in prostate cancer, allowing a process of adaptive radiotherapy with minimal physician workload. We present an analysis of PTV adequacy and a proposed adaptive process. METHODS AND MATERIALS: Tracking data were analyzed for 15 patients who underwent step-and-shoot multi-leaf collimation (SMLC) intensity-modulated radiation therapy (IMRT) with uniform 5-mm PTV margins for prostate cancer using the Calypso® Localization System. Additional plans were generated with 0- and 3-mm margins. A custom software application using the planned dose distribution and structure location from computed tomography (CT) simulation was developed to evaluate the dosimetric impact to the target due to motion. The dose delivered to the prostate was calculated for the initial three, five, and 10 fractions, and for the entire treatment. Treatment was accepted as adequate if the minimum delivered prostate dose (D(min)) was at least 98% of the planned D(min). RESULTS: For 0-, 3-, and 5-mm PTV margins, adequate treatment was obtained in 3 of 15, 12 of 15, and 15 of 15 patients, and the delivered D(min) ranged from 78% to 99%, 96% to 100%, and 99% to 100% of the planned D(min). Changes in D(min) did not correlate with magnitude of prostate motion. Treatment adequacy during the first 10 fractions predicted sufficient dose delivery for the entire treatment for all patients and margins. CONCLUSIONS: Our adaptive process successfully used real-time tracking data to predict the need for PTV modifications, without the added burden of physician contouring and image analysis. Our methods are applicable to other uses of real-time tracking, including hypofractionated treatment.

Effect of mid-scan breathing changes on quality of 4DCT using a commercial phase-based sorting algorithm.

PURPOSE: Though it is known that irregular breathing can introduce artifacts in commercial 4DCT, this has not been systematically explored. The purpose of this study is to investigate the effect of variations in basic parameters of the breathing wave on 4DCT imaging quality. METHODS: A four-dimensional motion platform holding an acrylic sphere was scanned while moving in a trajectory modeled from a lung cancer patient. A bellows device was used as a respiratory surrogate, and the images were sorted by a commercial phase-based sorting algorithm. Motion during the first half of the scan was produced at a baseline trajectory with a consistent frequency and amplitude of 15 breaths per minute and 1 cm, peak to peak. The two parameters were then varied mid-scan to new frequency and amplitude values, with frequencies ranging from 7.5 to 22 bpm and amplitudes ranging from 0.5 to 1.5 cm. Image sets representing four respiratory phases were contoured. Each set was analyzed to compare centroid displacement, density homogeneity, and volumetric and geometric distortions of the imaged sphere. Undercoverage of the target ITV and overcoverage of healthy tissue was also evaluated. RESULTS: Changes in amplitude of 25% or more, with or without changes in frequency, consistently caused measurable distortions in shape, position, and density of the imaged sphere. Frequency changes over 50% showed a similar trend. CONCLUSIONS: This study suggests that basic breathing statistics can be used to quickly assess the quality of a 4DCT scan prior to image reconstruction. Such information can help give indication of the proper course of action when irregular breathing patterns are observed during CT scanning.

Application of the continuity equation to a breathing motion model.

PURPOSE: To quantitatively test a breathing motion model using the continuity equation and clinical data. METHODS: The continuity equation was applied to a lung tissue and lung tumor free breathing motion model to quantitatively test the model performance. The model used tidal volume and airflow as the independent variables and the ratio of motion to tidal volume and motion to airflow were defined as alpha and beta vector fields, respectively. The continuity equation resulted in a prediction that the volume integral of the divergence of the alpha vector field was 1.11 for all patients. The integral of the divergence of the beta vector field was expected to be zero. RESULTS: For 35 patients, the alpha vector field prediction was 1.06 +/- 0.14, encompassing the expected value. For the beta vector field prediction, the average value was 0.02 +/- 0.03. CONCLUSIONS: These results provide quantitative evidence that the breathing motion model yields accurate predictions of breathing dynamics.

Characterization of free breathing patterns with 5D lung motion model.

PURPOSE: To determine the quiet respiration breathing motion model parameters for lung cancer and nonlung cancer patients. METHODS: 49 free breathing patient 4DCT image datasets (25 scans, cine mode) were collected with simultaneous quantitative spirometry. A cross-correlation registration technique was employed to track the lung tissue motion between scans. The registration results were applied to a lung motion model: X(-->) = X(-->)0 + alpha(-->)v + beta(-->)f, where X(-->) is the position of a piece of tissue located at reference position X(-->)0 during a reference breathing phase (zero tidal volume v, zero airflow f). alpha(-->) is a parameter that characterizes the motion due to air filling (motion as a function of tidal volume v) and beta(-->) is the parameter that accounts for the motion due to the imbalance of dynamical stress distributions during inspiration and exhalation that causes lung motion hysteresis (motion as a function of airflow f). The parameters alpha(-->) and beta(-->) together provide a quantitative characterization of breathing motion that inherently includes the complex hysteresis interplay. The alpha(-->) and beta(-->) distributions were examined for each patient to determine overall general patterns and interpatient pattern variations. RESULTS: For 44 patients, the greatest values of /alpha(-->)/ were observed in the inferior and posterior lungs. For the rest of the patients, /alpha(-->)/ reached its maximum in the anterior lung in three patients and the lateral lung in two patients. The hysteresis motion beta(-->) had greater variability, but for the majority of patients, /beta(-->)/ was largest in the lateral lungs. CONCLUSIONS: This is the first report of the three-dimensional breathing motion model parameters for a large cohort of patients. The model has the potential for noninvasively predicting lung motion. The majority of patients exhibited similar /alpha(-->)/ maps and the /beta(-->)/ maps showed greater interpatient variability. The motion parameter interpatient variability will inform our need for custom radiation therapy motion models. The utility of this model depends on the parameter stability over time, which is still under investigation.